Interpretable Machine Learning
نویسندگان
چکیده
The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand reasoning increasingly complex models. field IML (interpretable learning) grew out these concerns, with goal empowering various stakeholders tackle use cases, such building trust models, performing model debugging, and generally informing real human decision-making.
منابع مشابه
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ژورنال
عنوان ژورنال: ACM Queue
سال: 2021
ISSN: ['1542-7730', '1542-7749']
DOI: https://doi.org/10.1145/3511299